cdf | R Documentation |
This function computes the empirical scedasis distribution function.
cdf(Y, threshold = quantile(Y[, 2], 0.95))
Y |
data frame from which the estimate is to be computed; first column corresponds to time and the second to the variable of interest. |
threshold |
value used to threshold the data |
The empirical scedasis distribution function was introduced by Einmahl et al (2016).
C |
empirical scedasis distribution function. |
w |
standardized indices of exceedances. |
k |
number of exceedances above a threshold. |
Y |
raw data. |
The plot
method depicts the empirical cumulative scedasis
function, and the reference line for the case of constant frequency of
extremes over time (if uniform = TRUE
).
Miguel de Carvalho
Einmahl, J. H., Haan, L., and Zhou, C. (2016) Statistics of heteroscedastic extremes. Journal of the Royal Statistical Society: Ser. B, 78(1), 31–51.
data(sp500) attach(sp500) Y <- data.frame(date[-1], -diff(log(close))) fit <- cdf(Y) plot(fit) plot(fit, original = FALSE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.